Coded Language and ‘identity cleansing’ in Online Meme Hate Groups: Developments in Digital Cultural Criminology

• In Event: Cultural Criminology Continues

Abstract

Cultural criminology has long examined the crime-media nexus. This paper continues this tradition but extends the frame of analysis beyond the visual to include a focus on the relationship between images and a new ‘coded language’ evolving in the comment sections that accompany hateful/toxic memes. Drawing on data from a comprehensive digital ethnographic study (MOD Lab @University of Copenhagen), this paper shows how deliberately ambiguous, codified written expressions serve as a form of plausible deniability for hate speech supporters. More specifically, the research reveals how in-group communicative strategies—including feigned shock, performative disgust, and confused ambiguity—enable hate crime supporters to operate in two ways: First, by posting on clear web platforms just below the threshold of recognized online hate speech, and second, by masking support for hateful content behind insider argot and coded turns of phrase (including equivocal vernacular and specific emoji combinations). By examining these subcultural online practices, this paper contributes to digital criminology's ongoing discourse on techniques of neutralization and 'identity cleansing' in clear web environments.

Author

• Keith Hayward, University of Copenhagen